Prediction of protein loop geometries in solution

The ability to determine the structure of a protein in solution is a critical tool for structural biology, as proteins in their native state are found in aqueous environments. Using a physical chemistry based prediction protocol, we demonstrate the ability to reproduce protein loop geometries in experimentally derived solution structures. Predictions were run on loops drawn from (1)NMR entries in the Protein Databank (PDB), and from (2) the RECOORD database in which NMR entries from the PDB have been standardized and re-refined in explicit solvent. The predicted structures are validated by comparison with experimental distance restraints, a test of structural quality as defined by the WHAT IF structure validation program, root mean square deviation (RMSD) of the predicted loops to the original structural models, and comparison of precision of the original and predicted ensembles. Results show that for the RECOORD ensembles, the predicted loops are consistent with an average of 95%, 91%, and 87% of experimental restraints for the short, medium and long loops respectively. Prediction accuracy is strongly affected by the quality of the original models, with increases in the percentage of experimental restraints violated of 2% for the short loops, and 9% for both the medium and long loops in the PDB derived ensembles. We anticipate the application of our protocol to theoretical modeling of protein structures, such as fold recognition methods; as well as to experimental determination of protein structures, or segments, for which only sparse NMR restraint data is availabl

Hydrogen Bond Strengths in Phosphorylated and Sulfated Amino Acid Residues

<div><p>Post-translational modification by the addition of an oxoanion functional group, usually a phosphate group and less commonly a sulfate group, leads to diverse structural and functional consequences in protein systems. Building upon previous studies of the phosphoserine residue (pSer), we address the distinct nature of hydrogen bonding interactions in phosphotyrosine (pTyr) and sulfotyrosine (sTyr) residues. We derive partial charges for these modified residues and then study them in the context of molecular dynamics simulation of model tripeptides and sulfated protein complexes, potentials of mean force for interacting residue pairs, and a survey of the interactions of modified residues among experimental protein structures. Overall, our findings show that for pTyr, bidentate interactions with Arg are particularly dominant, as has been previously demonstrated for pSer. sTyr interactions with Arg are significantly weaker, even as compared to the same interactions made by the Glu residue. Our work sheds light on the distinct nature of these modified tyrosine residues, and provides a physical-chemical foundation for future studies with the goal of understanding their roles in systems of biological interest.</p> </div

Characterization of Hydrogen Bonds to Glu, pSer, pTyr, and sTyr in Experimental Protein Structures.

<p>Columns report the percentage of hydrogen bonds to Glu, pSer, pTyr or sTyr, that are to a given donor residue, and for Arg in a single or bidentate orientation. Residues were drawn from all structures in the Protein Databank containing a pSer, pTyr, or sTyr residue. For Glu, residues were taken from the set of structures containing a pSer residue.</p

Implicit Solvent Potentials of Mean Force for representative residue pairs.

<p>Plots show interaction energy vs. distance, at distance intervals of 0.25 Å, for a pair of residues in a given orientation. Distance refers to the P-C distance between the phosphate atom and the terminal carbon on Arg (coplanar), or the N-O distance (collinear).</p

Hydrogen Bond Occupancies in Molecular Dynamics Simulation of Tripeptide Systems.

<p>Columns report the percentage of frames showing a particular hydrogen bond for tripeptides Xxx-Gly-Yyy where Xxx represents hydrogen bonding donors Arg, Lys, or Gln; and Yyy represents Glu, pSer(−2), pSer(−1), pTyr(−2), pTyr(−1), or sTyr. For Arg tripeptides, the table reports percentages for single and bidentate interactions.</p

A comparison of electrostatic potentials for sTyr, pTyr(−1), and pTyr(−2).

<p>Electrostatic potentials are shown at isosurfaces of +/−2 kTe. The protonated phosphate group of pTyr(−1) presents a shaped charge that can provide a stronger interaction with hydrogen bond donors than the more isotropic charge on the sTyr sulfate.</p

Percentage of Glu, pSer, pTyr and sTyr residues showing a given number of hydrogen bonds.

<p>Residues were drawn from all structures in the Protein Databank containing a pSer, pTyr, or sTyr residue. For Glu, residues were taken from the set of structures containing a pSer residue.</p

Fraction of Free-Base Nicotine in Simulated Vaping Aerosol Particles Determined by X‑ray Spectroscopies

A new generation of electronic cigarettes is exacerbating the youth vaping epidemic by incorporating additives that increase the acidity of generated aerosols, which facilitate uptake of high nicotine levels. We need to better understand the chemical speciation of vaping aerosols to assess the impact of acidification. Here we used X-ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe the acid-base equilibria of nicotine in hydrated vaping aerosols. We show that, unlike the behavior observed in bulk water, nicotine in the core of aqueous particles was partially protonated when the pH of the nebulized solution was 10.4, with a fraction of free-base nicotine (αFB) of 0.34. Nicotine was further protonated by acidification with equimolar addition of benzoic acid (αFB = 0.17 at pH 6.2). By contrast, the degree of nicotine protonation at the particle surface was significantly lower, with 0.72 &lt; αFB &lt; 0.80 in the same pH range. The presence of propylene glycol and glycerol completely eliminated protonation of nicotine at the surface (αFB = 1) while not affecting significantly its acid-base equilibrium in the particle core. These results provide a better understanding of the role of acidifying additives in vaping aerosols, supporting public health policy interventions